Embodiments of the invention relate generally to diagnostic imaging and, more particularly, to a system and method for analyzing and visualizing spectral computed tomography (CT) data.
Typically, in CT imaging systems, an x-ray source emits a fan-shaped beam toward a subject or object, such as a patient or a piece of luggage. Hereinafter, the terms “subject” and “object” shall include anything capable of being imaged. The beam, after being attenuated by the subject, impinges upon an array of radiation detectors. The intensity of the attenuated beam radiation received at the detector array is typically dependent upon the attenuation of the x-ray beam by the subject. Each detector element of the detector array produces a separate electrical signal indicative of the attenuated beam received by each detector element. The electrical signals are transmitted to a data processing system for analysis that ultimately produces an image.
Generally, the x-ray source and the detector assembly are rotated about the gantry within an imaging plane and around the subject. X-ray sources typically include x-ray tubes, which emit the x-ray beam at a focal point. The detector assembly is typically made of a plurality of detector modules. Data representing the intensity of the received x-ray beam at each of the detector elements is collected across a range of gantry angles. The data are ultimately processed to form an image.
Conventional CT systems emit an x-ray with a polychromatic spectrum. The x-ray attenuation of each material in the subject depends on the energy of the emitted x-ray. If CT projection data is acquired at multiple x-ray energy levels or spectra, the data contains additional information about the subject or object being imaged that is not contained within a conventional CT image. For example, spectral CT data can be used to produce a new image with x-ray attenuation coefficients equivalent to a chosen monochromatic energy. Such a monochromatic image includes image data where the intensity values of the voxels are assigned as if a CT image were created by collecting projection data from the subject with a monochromatic x-ray beam.
A principle objective of energy sensitive scanning is to obtain diagnostic CT images that enhance information (contrast separation, material specificity, etc.) within the image by utilizing two or more scans at different chromatic energy states. A number of techniques have been proposed to achieve energy sensitive scanning including acquiring two or more scans either (1) back-to-back sequentially in time where the scans require multiple rotations of the gantry around the subject or (2) interleaved as a function of the rotation angle requiring one rotation around the subject, in which the tube operates at, for instance, 80 kVp and 140 kVp potentials.
High frequency generators have made it possible to switch the kVp potential of the high frequency electromagnetic energy projection source on alternating views. As a result, data for two or more energy sensitive scans may be obtained in a temporally interleaved fashion rather than two separate scans made several seconds apart as typically occurs with previous CT technology. The interleaved projection data may furthermore be registered so that the same path lengths are defined at each energy level using, for example, some form of interpolation.
Spectral CT data facilitates better discrimination of tissues, making it easier to differentiate between materials such as tissues containing calcium and iodine, for example. However, tissue behavior changes depending on a number of variables, such as patient thickness, contrast concentration and injection rate, timing of imaging, and tissue pathology. As such, the range and complexity of data available from spectral CT imaging makes the data difficult for a clinician to easily understand, interpret, discriminate, and make informed decisions. While known systems and methods can be employed to create and display monochromatic images, known systems and methods simply display images created using spectral CT data, and are lacking in regard to user interaction and analysis.
Further, making a diagnosis based on review of an image is a very specialized task and is typically performed by highly-trained medical image experts. However, even such experts can only make a subjective call as to the degree of severity of the disease. Due to this inherent subjectivity, the diagnoses tend to be inconsistent and non-standardized.
Accordingly, in order to use the data in a clinically relevant manner, there is a need for a methodology to compare spectral CT data across patients in a consistent fashion in spite of the above-described unavoidable and uncontrollable variables inherent in spectral CT data.
Therefore, it would be desirable to design a system and method of analyzing and visualizing spectral CT data that overcomes the aforementioned drawbacks.